Batteries are utilized in many traction and motive power applications to power electrical equipment and vehicles. Typical motive power applications include electric forklift trucks, reach trucks, pallet jacks, and automated guided vehicles.
In order to ensure proper operation of these vehicles, the batteries need to be charged regularly and may need to be monitored. Battery charging is the process of replenishing the discharged electrical energy from the electrical power network. This task is accomplished by employing battery chargers that are equipped with microprocessor controls to optimize the battery charging process.
Most battery chargers incorporate a power conversion stage for converting the incoming alternating current (AC) power from the electrical grid into a direct current (DC) power suitable for the battery. In addition, current chargers typically incorporate sense circuitry along with microprocessor controls to control the output current and voltage of the charger throughout the charge process, as well as save charge cycle records. Advanced chargers may also incorporate wired or wireless interfaces, such as RS-232, USB, ZigBee, Bluetooth, or WiFi, which allows end users to set up the charger parameters. The onboard microprocessor typically runs a firmware program that controls the charger operation, stores data, and communicates with a computer or handheld device to receive new charger set points.
Battery monitoring may also be desirable to monitor the status of batteries to ensure proper battery health and performance. A typical battery monitoring unit typically incorporates a microprocessor, memory for data storage, sensing circuitry, and some wired or wireless interface to set up the unit and download stored parameters. The battery monitor measures and stores battery voltage, battery current, battery temperature, and battery amp-hours throughout the charge and discharge (use) cycles. In addition, various settings are typically stored in these battery monitoring units including battery size, nameplate rating, battery ID and serial number, among other things. The battery monitor onboard microprocessor typically runs a firmware program that controls the charger operation, stores data, and communicates with a computer or handheld device to receive new charger set points and download stored data.
In most applications, the battery is sized to power an industrial truck for a single shift. As such, in multi-shift applications, battery changing may be desirable. This typically requires more than one battery per truck to power the truck throughout the day. When a depleted battery is removed from the truck, it is typically placed on a rack to be charged. Typical battery racks may have anywhere from a few batteries to hundreds of batteries stacked on shelves with chargers connected to each battery. Battery charging can take approximately eight (8) hours followed by a cool down period of a few hours. As battery racks may have multiple batteries connected to the chargers, the task of selecting the ready battery, namely a charged or a rested battery, can be daunting.
Battery light indicators have been used to alert users to batteries that are ready to be used for the next truck. However, in applications with large numbers of trucks and batteries, identifying the state of lights installed on each battery can be very difficult.
Battery management systems have been used to simplify the process of selecting the next battery that is ready to be used. These battery management systems typically include sensing devices (battery sensors) that are installed at the charger side (connected to the charger cable) that detect whether a battery is connected or not. These sensors are typically equipped with daisy chained communication ports (links) that ultimately connect to a central controller. Each sensor is assigned to a specific charger and specific battery bay with racks, where a given battery is placed. The combination of the central controller along with the battery sensors track connectivity of batteries, charge process, and duration of charge termination to identify the order of batteries to be selected. These systems may include visual and audio alerts notifying users which battery to select and/or alerting users when selecting the wrong battery.
One of the main drawbacks of most battery management systems is the cost involved in installing the added hardware and software to manage these batteries. Typical systems can costs thousands to tens of thousands of dollars, making their deployment limited to customers with very large fleets. In addition, many of the analytics and decisions made by these systems is limited as batteries cannot be uniquely identified. For example, if multiple batteries are ready to be selected, the system simply selects the first battery that reported being ready (first-in-first-out or FIFO system).
Another limitation of most battery management systems is that they are add-on devices that are separate from the chargers and do not report any charger status. For example, if the charge cycle did not terminate correctly due to battery fault or charger fault, the battery management system may still list the battery as being ready for use. In fact, since most batteries in use are flooded lead acid batteries, many of these batteries may require watering after a charge cycle to ensure proper operation. Yet, most battery management systems cannot even identify the batteries, and hence cannot assess any battery status issues.
Due to the drawbacks of many existing battery management systems, further improvements may be desirable for a cloud based battery management system.